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1. Operating Systems: CSE 3204
ASTU
Department of CSE
Lecture 5: Process Synchronization
Chapter Two
Process Management

2. Content
 Background of Process Synchronization
 The Critical-Section Problem
 Classic Problems of Synchronization
 Semaphores
 Monitors

3. • Concurrent Processes can be
• Independent processes
• cannot affect or be affected by the execution of another process.
• Cooperating processes
• can affect or be affected by the execution of another process.
• Cooperating processes can either share directly similar address space or
share data through files and messages.
• Concurrent access to shared data may lead to data inconsistency.
• Concurrent execution requires
• process communication and process synchronization
 Process Synchronization
• …mechanisms to ensure the orderly execution of cooperating processes
that share a logical address space, so that data consistency is
maintained.
Background to Process Synchronization
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4. • Concurrent processes may have access to shared data and
resources
• Concurrent access to shared data may result in data inconsistency
• If there is no controlled access to shared data, some processes will
obtain an inconsistent view of the shared data
 Consider two processes P1 and P2, accessing shared data. while
P1 is updating data, it is preempted (because of timeout, for
example) so that P2 can run. Then P2 try to read the data, which
are partly modified, which will result in data inconsistency
• In such cases, the outcome of the action performed by concurrent
processes will then depend on the order in which their execution is
interleaved
• Maintaining data consistency requires mechanisms to ensure the
orderly execution of cooperating processes
Background to Process synchronization
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5. Synchronization in Producer-Consumer Problem
• producer process produces information that is consumed by a
consumer process.
• The previous solution considered the use of a bounded buffer
• Producer produce items and puts it into the buffer
• Consumer consumes items from the buffer
• Producer and Consumer must synchronize.
• Suppose that we wanted to provide a solution to the consumer-
producer problem that fills all the buffers.
• We can do so by having an integer count that keeps track of the
number of full buffers.
• Initially, count is set to 0.
• It is incremented by the producer after it produces a new buffer
• It is decremented by the consumer after it consumes a buffer
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6. Producer - Consumer Problem
Producer
while (true)
{
/* produce an item and put in
nextProduced */
while (count == BUFFER_SIZE)
; // do nothing
buffer [in] = nextProduced;
in = (in + 1) % BUFFER_SIZE;
count++;
}
Consumer
while (true)
{
while (count == 0)
; // do nothing
nextConsumed = buffer[out];
out = (out + 1) % BUFFER_SIZE;
count--;
/* consume the item innextConsumed
}
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• Although both producer and consumer routines are correct when executed
separately, they may not properly work when executed concurrently.
•To illustrate this, let’s assume the current value of the count variable is 5

7. • count++ could be implemented as (in a typical machine language):
register1 = count
register1 = register1 + 1
count = register1
• count-- could be implemented as (in a typical machine language):
register2 = count
register2 = register2 - 1
count = register2
• The concurrent execution of count ++ and count -- is equivalent with the execution
of the statements of each operations where arbitrary interleaving of the statements
occur. A simple arbitrary interleaving of the operations can be as follows:
S0: producer execute register1 = count {register1 = 5}
S1: producer execute register1 = register1 + 1 {register1 = 6}
S2: consumer execute register2 = count {register2 = 5}
S3: consumer execute register2 = register2 - 1 {register2 = 4}
S4: producer execute count = register1 {count = 6 }
S5: consumer execute count = register2 {count = 4}
•At S5, we have arrived at the value of counter=4, if we reversed S4 and S5,
we would have arrived at count=6
•We would arrive at the incorrect value of the count variable because we allowed
both processes to manipulate the variable concurrently
Producer Consumer Problem (cont’d)
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8. Race condition
• Race condition is the situation where several processes access
and manipulate shared data concurrently
• The final value of the shared data depends upon which process
finishes last.
• The key to preventing trouble here and in many other situations
involving shared memory, shared files, and shared everything
else is to find some way to prohibit more than one process from
reading and writing the shared data at the same time .
• To prevent race conditions, concurrent processes must
coordinate or be synchronized.
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9. Example: Race condition updating a variable
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10. The Critical-Section Problem
• n processes competing to use some shared data
• Each process has a code segment, called Critical Section (CS), in which the
shared data is accessed
• A critical section is a piece of code in which a process or thread accesses a
common resource
• So each process must first request permission to enter its critical section.
The section of code implementing this request is called the Entry Section
(ES)
• The critical section (CS) might be followed by a Leave/Exit Section (LS)
• The remaining code is the Remainder Section (RS)
• Problem – ensure that when one process is executing in its CS, no other
process is allowed to execute in its CS
• When a process executes code that manipulates shared data (or resource), we
say that the process is in it’s Critical Section (for that shared data)
• The execution of critical sections must be mutually exclusive: at any time,
only one process is allowed to execute in its critical section (even with multiple
processors) 10
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11. Critical section to prevent a race condition
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 Multiprogramming allows logical parallelism, uses devices efficiently
but we lose correctness when there is a race condition.
 So we forbid logical parallelism inside critical section so we lose some
parallelism but we regain correctness.

12.  So each process must first request permission to enter its critical section.
 The section of code implementing this request is called the Entry Section
(ES).
 The critical section (CS) might be followed by a Leave/Exit Section
(LS).
 The remaining code is the Remainder Section (RS).
 The critical section problem is to design a protocol that the processes can
use so that their action will not depend on the order in which their
execution is interleaved (possibly on many processors).
• General structure of process Pi (other process Pj)
do {
entry section
critical section
leave/exit section
reminder section
} while (1);
The Critical-Section Problem(cont…)

13. • A solution to a critical section problem must satisfy the following three
requirements:
1.Mutual Exclusion - If process Pi is executing in its critical section, then no
other processes can be executing in their critical sections
2.Progress - If no process is executing in its critical section and there exist
some processes that wish to enter their critical section, then the selection of
the processes that will enter the critical section next cannot be postponed
indefinitely. Then only those processes that are not executed in their
remainder sections can participate in the decision on which will enter its
critical section next.
3.Bounded Waiting - A bound must exist on the number of times that other
processes are allowed to enter their critical sections after a process has
made a request to enter its critical section and before that request is
granted
 Assume that each process executes at a nonzero speed
 No assumption concerning relative speed of the N processes
Solution to critical section problem
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14. Advantages
• Applicable to any number of processes on either a single processor or
multiple processors sharing main memory
• It is simple and therefore easy to verify
• It can be used to support multiple critical sections
Disadvantages
• Busy-waiting consumes processor time
• Starvation is possible when a process leaves a critical section and
more than one process is waiting
• Deadlock
• If a low priority process has the critical region and a higher priority
process needs, the higher priority process will obtain the
processor(CPU) to wait for the critical region
Solution to CS problem: Mutual Exclusion
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15. • A Special variable, S called a semaphore if it is
used for signaling
• Semaphore is a variable that has an integer value
• May be initialized to a nonnegative number
• Wait operation decrements the semaphore
value
• Signal operation increments semaphore value
• Two standard operations modify S: wait ( ) and
signal ( )
• Wait and signal operations cannot be interrupted
• Queue is used to hold processes waiting on the
semaphore
• If a process is waiting for a signal, it is suspended
until that signal is sent
wait (S) {
while S <= 0
; // no-op
S--;
}
signal (S) {
S++;
}
Semaphore
• Less complicated than the hardware based solutions (using TESTandSET() and
swap ( ) instructions
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16.  Two Types of Semaphores
• Counting semaphore – integer value can
range over an unrestricted domain
• Binary semaphore – integer value can range
only between 0 and 1; can be simpler to
implement
• Also known as mutex locks
• Can implement a counting semaphore S as a
binary semaphore
• Provides mutual exclusion
• Modifications to the integer value of the
semaphore in the wait and signal operations must
be executed indivisibly.
Semaphore S;
// initialized to 1
wait (S);
Critical Section
signal (S);
Semaphores as General Synchronization Tool
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17. Semaphore Implementation
• Must guarantee that no two processes can execute wait () and
signal () on the same semaphore at the same time
• Thus, implementation becomes the critical section problem where
the wait and signal code are placed in the critical section
• Could now have busy waiting in critical section implementation
• But implementation code of the critical section is short
• Little busy waiting if critical section rarely occupied
• Note that applications may spend lots of time in critical sections
and therefore this is not a good solution
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18. Semaphore Implementation with no Busy waiting
• With each semaphore there is an
associated waiting queue. Each entry in a
waiting queue has two data items:
• value (of type integer)
• pointer to next record in the list
• Two operations:
• block – place the process invoking the
operation on the appropriate
waiting queue.
• wakeup – remove one of the processes
in the waiting queue and place it in the
ready queue.
 Implementation of wait:
wait (S){
value--;
if (value < 0) {
add this process to waiting
queue
block(); }
}
 Implementation of signal:
Signal (S){
value++;
if (value <= 0) {
remove a process P from the
waiting queue
wakeup(P); }
}
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19. • Semaphores provide a powerful tool for enforcing mutual exclusion and
coordinate processes, But wait (S) and signal (S) are scattered among
several processes. Hence, difficult to understand their effects
• Usage must be correct in all the processes (correct order, correct variables,
no omissions)
• One bad (or malicious) process can fail the entire collection of processes
• Deadlock and Starvation
• Deadlock – two or more processes are waiting indefinitely for an event
that can be caused by only one of the waiting processes.
Let S and Q be two semaphores initialized to 1
P0 P1
wait(S); wait(Q);
wait(Q); wait(S);
 
signal(S); signal(Q);
signal(Q) signal(S);
• Starvation – indefinite blocking. A process may never be removed from
the semaphore queue in which it is suspended.
Problems with Semaphores
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20. Classical Problems of Synchronization
• Bounded-Buffer Problem
• Readers and Writers Problem
• Dining-Philosophers Problem
• The Sleeping Barber Problem
(Read Chapter 6.6 of the text book)
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21. Bounded-Buffer Problem
• N buffers, each can hold one item
• Semaphore mutex initialized to the value 1
• Semaphore full initialized to the value 0
• Semaphore empty initialized to the value N.
 The structure of the producer process
while (true) {
// produce an item
wait (empty);
wait (mutex);
// add the item to the buffer
signal (mutex);
signal (full);
}
 The structure of the consumer process
while (true) {
wait (full);
wait (mutex);
// remove an item from buffer
signal (mutex);
signal (empty);
// consume the removed
item
}

22. Readers-Writers Problem
• A data set is shared among a number of concurrent processes
• Readers – only read the data set; they do not perform any
updates
• Writers – can both read and write.
Problem – allow multiple readers to read at the same time. Only
one single writer can access the shared data at the same time.
• Shared Data
• Data set
• Semaphore mutex initialized to 1.
• Semaphore wrt initialized to 1.
• Integer readcount initialized to 0.

23. Readers-Writers Problem (Cont.)
 The structure of a writer process
while (true) {
wait (wrt) ;
// writing is performed
signal (wrt) ;
}
 The structure of a reader process
while (true) {
wait (mutex) ;
readcount ++ ;
if (readcount == 1) wait (wrt) ;
signal (mutex)
// reading is performed
wait (mutex) ;
readcount - - ;
if (readcount == 0) signal (wrt) ;
signal (mutex) ;
}

24. Dining-Philosophers Problem
• Shared data
• Bowl of rice (data set)
• Semaphore chopstick [5] initialized to 1

25. Dining-Philosophers Problem (Cont.)
• The structure of Philosopher i:
While (true) {
wait ( chopstick[i] );
wait ( chopStick[ (i + 1) % 5] );
// eat
signal ( chopstick[i] );
signal (chopstick[ (i + 1) % 5] );
// think
}

26. Problems with Semaphores
• Incorrect use of semaphore operations:
• signal (mutex) …. wait (mutex)
• wait (mutex) … wait (mutex)
• Omitting of wait (mutex) or signal (mutex)
(or both)

27. Monitors
• A high-level abstraction that provides a convenient and effective
mechanism for process synchronization
• A monitor is a software module consisting of sets of procedures and local
data variables
• The main characteristics of monitors are:
 Local variables of a monitor are only accessible by the monitor’s
procedures (no external procedure can access variables of the
monitor)
 Only one process may be active within the monitor at a time
 A process enters the monitor by invoking one of its procedures
 By only allowing one process to execute at a time, the monitor
provides a mutual exclusion facility
 Thus, a shared data structure can be included as part of a monitor
and will be protected
 If the data in the monitor represents a shared resource, then the
monitor provides a mutual exclusion facility on the resource
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28. Monitor (contd.)
monitor monitor-name
{
// shared variable
declarations
procedure P1 (…) { …. }
…
procedure Pn (…) {……}
Initialization code ( ….) { … }
…
}
}
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29. Monitors: Condition Variables
• A monitor supports synchronization by the use of condition variables
that are contained within the monitor and accessible only within the
monitor
• Condition variables are a special data type in monitors,
• Conditon x, y;
• The only operations that can be invoked on condition variables are wait()
and signal()
• The operation x.wait () means a process that invokes the operation is
suspended until another process invokes the x.signal() operation
• x.signal () – resumes one of the suspended processes. If there are no
suspended operations, then the operation will have no effect.
• Note that: The wait() and signal() operations in monitor and semaphore
are different. If a process in a monitor signals and no task is waiting on
the condition variable, the signal is lost. However, in semaphores, the
signal operation will always have effect on the state/value of the
semaphore variable.
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30. Reading Assignments
 Software Solutions to Synchronization problems
• Peterson’s solution
 Hardware based solutions
• Swap
• Test and Set
• Lock